Therapeutic cancer vaccines

Nature reviews. Cancer, Journal Year: 2021, Volume and Issue: 21(6), P. 360 - 378

Published: April 27, 2021

Language: Английский

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NAD+ metabolism and its roles in cellular processes during ageing

Nature Reviews Molecular Cell Biology, Journal Year: 2020, Volume and Issue: 22(2), P. 119 - 141

Published: Dec. 22, 2020

Language: Английский

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Macrophages in immunoregulation and therapeutics

Signal Transduction and Targeted Therapy, Journal Year: 2023, Volume and Issue: 8(1)

Published: May 22, 2023

Abstract Macrophages exist in various tissues, several body cavities, and around mucosal surfaces are a vital part of the innate immune system for host defense against many pathogens cancers. possess binary M1/M2 macrophage polarization settings, which perform central role an array tasks via intrinsic signal cascades and, therefore, must be precisely regulated. Many crucial questions about signaling modulation yet to uncovered. In addition, clinical importance tumor-associated macrophages is becoming more widely recognized as significant progress has been made understanding their biology. Moreover, they integral tumor microenvironment, playing regulation wide variety processes including angiogenesis, extracellular matrix transformation, cancer cell proliferation, metastasis, immunosuppression, resistance chemotherapeutic checkpoint blockade immunotherapies. Herein, we discuss signaling, mechanical stresses modulation, metabolic pathways, mitochondrial transcriptional, epigenetic regulation. Furthermore, have broadly extended traps essential roles autophagy aging regulating functions. discussed recent advances macrophages-mediated autoimmune diseases tumorigenesis. Lastly, targeted therapy portray prospective targets therapeutic strategies health diseases.

Language: Английский

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The application of nanoparticles in cancer immunotherapy: Targeting tumor microenvironment

Bioactive Materials, Journal Year: 2020, Volume and Issue: 6(7), P. 1973 - 1987

Published: Dec. 26, 2020

The tumor development and metastasis are closely related to the structure function of microenvironment (TME). Recently, TME modulation strategies have attracted much attention in cancer immunotherapy. Despite preliminary success immunotherapeutic agents, their therapeutic effects been restricted by limited retention time drugs TME. Compared with traditional delivery systems, nanoparticles unique physical properties elaborate design can efficiently penetrate specifically deliver major components In this review, we briefly introduce substitutes including dendritic cells, macrophages, fibroblasts, vasculature, tumor-draining lymph nodes hypoxic state, then review various targeting these applications therapy. addition, could be combined other therapies, chemotherapy, radiotherapy, photodynamic therapy, however, nanoplatform system may not effective all types tumors due heterogeneity different individuals. changes at stages during required further elucidated so that more individualized nanoplatforms designed.

Language: Английский

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Redefining Tumor-Associated Macrophage Subpopulations and Functions in the Tumor Microenvironment

Frontiers in Immunology, Journal Year: 2020, Volume and Issue: 11

Published: Aug. 4, 2020

The immunosuppressive status of the tumour microenvironment (TME) remains poorly defined due to a lack understanding regarding function tumour-associated macrophages (TAMs), which are abundant in TME. TAMs crucial drivers progression, metastasis and resistance therapy. Intra- inter-tumoural spatial heterogeneities potential keys relationships between subpopulations their functions. Antitumour M1-like pro-tumour M2-like coexist within tumours, opposing effects these M1/M2 on tumours directly impact current strategies improve antitumour immune responses. Recent studies have found significant differences among monocytes or from distinct other investigations explored existence diverse TAM subsets at molecular level. In this review, we discuss emerging evidence highlighting redefinition functions TME possibility separating macrophage with into during development tumours. Such may relate differential cellular origin monocyte plasticity heterogeneity TAMs, all potentially biomarkers our how phenotypes dictated by ontogeny, activation localization. Therefore, detailed landscape must be deciphered integration new technologies, such as multiplexed immunohistochemistry (mIHC), mass cytometry time-of-flight (CyTOF), single-cell RNA-seq (scRNA-seq), transcriptomics systems biology approaches, for analyses

Language: Английский

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Targeting macrophages in cancer immunotherapy

Signal Transduction and Targeted Therapy, Journal Year: 2021, Volume and Issue: 6(1)

Published: March 26, 2021

Abstract Immunotherapy is regarded as the most promising treatment for cancers. Various cancer immunotherapies, including adoptive cellular immunotherapy, tumor vaccines, antibodies, immune checkpoint inhibitors, and small-molecule have achieved certain successes. In this review, we summarize role of macrophages in current immunotherapies advantages targeting macrophages. To better understand make use type cell, their development differentiation characteristics, categories, typical markers, functions were collated at beginning review. Therapeutic strategies based on or combined with potential to improve efficacy therapies.

Language: Английский

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Dendritic Cells and Their Role in Immunotherapy

Frontiers in Immunology, Journal Year: 2020, Volume and Issue: 11

Published: May 21, 2020

Despite significant advances in the field of cancer immunotherapy, majority patients still do not benefit from treatment and must rely on traditional therapies. Dendritic cells have long been a focus immunotherapy due to their role inducing protective adaptive immunity, but vaccines shown limited efficacy past. With advent immune checkpoint blockade ability identify patient-specific neoantigens, new combinatorial therapies are being evaluated clinic. also emerging as critical regulators response with tumors. Understanding how augment function these intratumoral dendritic could offer approaches enhance addition improving cytotoxic targeted that partially dependent upon robust for efficacy. Here we will discuss specific cell subsets regulating anti-tumor response, well current status cell-based immunotherapies, order provide an overview future lines research clinical trials.

Language: Английский

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Current perspectives on the immunosuppressive tumor microenvironment in hepatocellular carcinoma: challenges and opportunities

Molecular Cancer, Journal Year: 2019, Volume and Issue: 18(1)

Published: Aug. 29, 2019

Incidence of hepatocellular carcinoma (HCC) is on the rise due to prevalence chronic hepatitis and cirrhosis. Although there are surgical chemotherapy treatment avenues mortality rate HCC remains high. Immunotherapy currently new frontier cancer immunobiology emerging as an area for further exploration. The tumor microenvironment coexists interacts with various immune cells sustain growth HCC. Thus, immunosuppressive play important role in anti-tumor response. This review will discuss current concepts cells, including tumor-associated macrophages, marrow-derived suppressor neutrophils, cancer-associated fibroblasts, regulatory T cell interactions actively promote tumorigenesis. It elaborates modalities future areas

Language: Английский

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Macrophage diversity in cancer revisited in the era of single-cell omics

Trends in Immunology, Journal Year: 2022, Volume and Issue: 43(7), P. 546 - 563

Published: June 9, 2022

TAMs have diverse functions in cancer, reflecting the heterogenous nature of these immune cells. Here, we propose a new nomenclature to identify TAM subsets.Recent single cell multi-omics technologies, which allow clustering subsets an unbiased manner, significantly advanced our understanding molecular diversity mice and humans.Novel mechanisms potential therapeutic targets been identified that might regulate tumor-promoting function different subsets.TAM opens promising opportunities for envisaging putative cancer treatments. Tumor-associated macrophages (TAMs) multiple potent and, thus, represent important targets. These highlight TAMs. Recent omics technologies However, unifying annotation their signatures is lacking. review recent major studies transcriptome, epigenome, metabolome, spatial with specific focus on We also consensus model present avenues future research. one most abundant types tumors [1.Cassetta L. Pollard J.W. Targeting macrophages: approaches cancer.Nat. Rev. Drug Discov. 2018; 17: 887-904Crossref PubMed Scopus (650) Google Scholar]. Since initial decade ago [2.Qian B.Z. Macrophage enhances tumor progression metastasis.Cell. 2010; 141: 39-51Abstract Full Text PDF (3151) Scholar], functional now widely appreciated, many seminal field [3.Yang M. et al.Diverse microenvironments.Cancer Res. 78: 5492-5503Crossref (202) Scholar, 4.DeNardo D.G. Ruffell B. Macrophages as regulators tumour immunity immunotherapy.Nat. Immunol. 2019; 19: 369-382Crossref (643) 5.Lopez-Yrigoyen al.Macrophage targeting cancer.Ann. N. Y. Acad. Sci. 2021; 1499: 18-41Crossref (25) This array includes promotion growth, lineage plasticity, invasion, remodeling extracellular matrix, crosstalk endothelial, mesenchymal stromal cells, other cells; effects can result progression, metastasis (see Glossary), therapy resistance [6.Mantovani A. al.Tumour-associated treatment oncology.Nat. Clin. Oncol. 2017; 14: 399-416Crossref (1675) Scholar,7.Guc E. Redefining macrophage neutrophil biology metastatic cascade.Immunity. 54: 885-902Abstract (13) With wide application years seen explosion data illustrating cellular heterogeneity resulting unprecedented amount information TAMs, regardless main studies. Links between are emerging. terminology lacking, making direct comparisons full utilization sets difficult. In this review, summarize human data; include traditional nomenclatures, at levels single-cell transcriptomic, epigenomic, metabolic multi-omics, opportunities, directions. subsets. hope will serve starting point help build complete picture dynamic interactions tumor, well microenvironment (TME). A used describe has now-obsolete M1/M2 model, proposed ~20 ago; it separated into two distinct arms: M1 or 'classically' activated; M2 'alternatively' activated, largely based vitro stimulating type 1 2 cytokines [8.Mills C.D. al.M-1/M-2 Th1/Th2 paradigm.J. 2000; 164: 6166-6173Crossref The newer term 'M1-like' phenotype typically described proinflammatory induced by Toll-like receptor (TLR) ligands cytokines, namely IFN-γ TNF-α. Conversely, 'M2-like' having anti-inflammatory characteristics, being activated interleukin (IL)-4 IL-13, producing TGF-β profibrotic factors. nomenclature, albeit used, remains oversimplified [9.Martinez F.O. Gordon S. paradigm activation: time reassessment.F1000Prime Rep. 2014; 6: 13Crossref (2673) Scholar,10.Nahrendorf Swirski F.K. Abandoning network function.Circ. 2016; 119: 414-417Crossref (195) Indeed, significant morphology, function, surface marker expression observed resident-tissue (RTMs) from organs [11.Bleriot C. al.Determinants resident tissue identity function.Immunity. 2020; 52: 957-970Abstract (94) Scholar]; moreover, co-expression both gene almost all [12.Mulder K. al.Cross-tissue landscape monocytes health disease.Immunity. 1883-1900Abstract Therefore, spectrum polarization relates represents more sensible approach describing [10.Nahrendorf Scholar,13.Mosser D.M. Edwards J.P. Exploring activation.Nat. 2008; 8: 958-969Crossref (5864) normal homeostasis, tightly regulated niche-like local environment, recently [14.Guilliams al.Establishment maintenance niche.Immunity. 434-451Abstract (138) Another layer derives origin. Using lineage-tracing mice, illustrated mouse RTMs derived early erythromyeloid progenitors formed either yolk sac fetal liver [15.Geissmann F. al.Blood consist principal migratory properties.Immunity. 2003; 71-82Abstract (2514) Scholar,16.Gomez Perdiguero al.Tissue-resident originate yolk-sac-derived erythro-myeloid progenitors.Nature. 2015; 518: 547-551Crossref (1236) Additionally, adult may derive circulating monocytic precursors (monocytes) bone marrow [17.Cox al.Origins, biology, diseases macrophages.Annu. 39: 313-344Crossref (1) monocyte contribution varies among organs. For example, steady state, microglia central nervous system (CNS) solely [18.Hoeffel G. al.C-Myb(+) progenitor-derived give rise tissue-resident macrophages.Immunity. 42: 665-678Abstract (611) while dermal embryonic origin [19.Kolter J. al.A subset skin contributes surveillance regeneration nerves.Immunity. 50: 1482-1497Abstract (69) appreciated repeatedly reviewed [20.Pathria P. al.Targeting tumor-associated cancer.Trends 40: 310-327Abstract (382) Scholar,21.Guerriero J.L. Macrophages: road less traveled, changing anticancer therapy.Trends Mol. Med. 24: 472-489Abstract (143) Similar counterparts not only its ontogeny, but cues, including type, organ, subanatomic Identifying basis over past [5.Lopez-Yrigoyen advancements unveiling multidimensional complexity manner. research, oncology eventually fully understand cells hopefully use improve precision diagnosis therapy. Single RNA sequencing (scRNA-seq) technology revolutionized providing in-depth transcriptome level [22.Giladi al.Single-cell characterization haematopoietic trajectories homeostasis perturbed haematopoiesis.Nat. Cell Biol. 20: 836-846Crossref (139) substantial advances available experimental techniques bioinformatics pipelines years, scRNA-seq investigate [23.Lawson D.A. al.Tumour resolution.Nat. 1349-1360Crossref (230) Scholar,24.Ren X. al.Insights gained analysis microenvironment.Annu. 583-609Crossref (15) transcriptomic remain Two large-scale pan-cancer provided valuable regarding diversity. One study analyzed myeloid 380 samples across 15 210 patients through combination newly collected eight published [25.Cheng transcriptional atlas infiltrating cells.Cell. 184: 792-809Abstract (111) Comparison consistent presence CD14+ CD16+ tumor-infiltrating (TIMs), LYVE1+ interstitial non-cancer tissues, seven clusters: INHBA+ C1QC+ ISG15+ LNRP3+ SPP1+ compiled mononuclear phagocytes (MNPs) isolated 41 13 types, six common universe, termed MNP-VERSE. Monocyte clusters were then extracted reintegrated generate MoMac-VERSEi. regulatory inference (SCENIC) [26.Aibar al.SCENIC: clustering.Nat. Methods. 1083-1086Crossref (1003) authors classical monocytes, nonclassical five (HES1 TAM, C1Qhi TREM2 IL4I1 proliferating TAMs) Although nomenclatures studies, others, pattern transcriptomics By reviewing journals, found preserved (Table 1). Based signature genes, enriched pathways, predicated naming interferon-primed (IFN-TAMs), (Reg-TAMs), inflammatory cytokine-enriched (Inflam-TAMs), lipid-associated (LA-TAMs), pro-angiogenic (Angio-TAMs), RTM-like (RTM-TAMs), (Prolif-TAMs) Figure 1, Key figure). Furthermore, three TIMs Box 1).Table 1Mouse various TMEsaBlack font: genes clusters; blue protein markers Underline: CITE-seq; Bold: key reported than paper., bAbbreviations: BRCA, breast cancer; CAF, cancer-associated macrophage; CITE-seq, indexing transcriptomes epitopes sequencing; CRC, colorectal CyTOF, Mass cytometry flight; ECM, matrix; ESCA, esophageal carcinoma; GC, gastric HCC, hepatocellular HNC, head neck i.v., intravenous; IF, immunofluorescent staining; INs-seq, intracellular staining LCM, laser capture microdissection; LYM, lymphoma; MEL, melanoma; Mets, metastasis; mIHC, multiplex immunochemistry MMY, myeloma; N/A, available; NPC, nasopharyngeal NSCLC, nonsmall lung OS, osteosarcoma; OVC, ovarian PDAC, pancreatic ductal adenocarcinoma; PRAC, prostate RCC, renal Reg-TAMs, TAMs; SARC, sarcoma; sc-MS, mass spectrometry; SEPN, spinal ependymomas; SKC, ST, transcriptomics; s.c., subcutaneous; macrophages; THCA, thyroid UCEC, uterine corpus endometrial carcinoma.AnnotationSpeciesSignatureTFCancer typeFunction/enriched pathwayAssayRefsIFN-TAMsHumanCASP1, CASP4, CCL2/3/4/7/8, CD274hi, CD40, CXCL2/3/9/10/11, IDO1, IFI6, IFIT1/2/3, IFITM1/3, IRF1, IRF7, ISG15, LAMP3, PDCD1LG2hi, TNFSF10, C1QA/C, CD38, IL4I1, IFI44LSTAT1 IRF1/7BRCACRCCRC metsGBMHCCHNCLYMMELMMYNPCNSCLCOSPDACSEPNTHCAUCECApoptosis regulatorsEnhance proliferationInflammatory responsesPromote Treg entry tumorT exhaustionImmunosuppressionColocalization exhausted T (ST, IF)Decreased antigen presentation (CyTOF)Suppressed activation (in vitro)IFN-α/γ-IFN response signature; IL2/STAT5; IL6/JAK/STAT3scRNA-seqCITE-seqmIHCSTNanoString GeoMx[12.Mulder Scholar,29.Gubin M.M. al.High-dimensional delineates lymphoid compartment during successful immune-checkpoint therapy.Cell. 175: 1014-1030Abstract (165) Scholar,32.Zavidij O. reveals compromised precursor stages myeloma.Nat. Cancer. 1: 493-506Crossref 33.Zhou intratumoral immunosuppressive osteosarcoma.Nat. Commun. 11: 6322Crossref (74) 34.Zhang Q. al.Interrogation microenvironmental ependymomas dual macrophages.Nat. 12: 6867Crossref (0) Scholar,45.Wu al.Spatiotemporal level.Cancer 134-153Crossref (10) Scholar,52.Pombo Antunes A.R. profiling glioblastoma species disease stage competition specialization.Nat. Neurosci. 595-610Crossref (78) Scholar,\81.Wu S.Z. spatially resolved cancers.Nat. Genet. 53: 1334-1347Crossref (47) Scholar,83.Pelka al.Spatially organized multicellular hubs cancer.Cell. 4734-4752Abstract (29) Scholar]CD14+, CD11b+, CD68+, PD-L1hi, PD-L2hi, CD80hi, CD86hi, MHCIIhi, CD86+, MRC1–, SIGLEC1–, HLA-DRlo, CD314+, CD107a+, CD86, TLR4, CD44 (CITE-seq)MouseCcl2/7/8, Cd274, Cxcl9/10/11, Ifit1/2/3, Ifit3, Ifitm1/3, Il7r, Isg15, Nos2, Rsad2, Tnfsf10, Stat1N/ACT26 s.c. CRCCT26 intrasplenic mets modelT3 SARC (s.c.)Orthotopic GL261 GBMIFN signaturescRNA-seqCITE-seqmIHC[29.Gubin Scholar]Inflam-TAMsHumanCCL2/3/4/5/20, CCL3L1, CCL3L3, CCL4L2, CCL4L4, CXCL1/2/3/5/8, G0S2, IL1B, IL1RN, IL6, INHBA, KLF2/6, NEDD9, PMAIP1, S100A8/A9, SPP1EGR3 IKZF1 NFKB1 NFE2L2 RELCRCCRC metsOSSEPNGCRecruiting regulating cellsCNS inflammation-associated chemokinesPromotes inflammationNeutrophil recruitment lumenT interaction (IHC)TNF signaling; WNTImmune check pointsscRNA-seqmIHCNanoString GeoMx[31.Che L.-H. metastases reprogramming preoperative chemotherapy.Cell Discovery. 7: 80Crossref (4) Scholar,33.Zhou Scholar,34.Zhang Scholar,42.Sathe genomic microenvironment.Clin. Cancer 26: 2640-2653Crossref (66) 43.Zhang al.Dissecting underlying premalignant lesions cancer.Cell 27: 1934-1947Abstract (104) 44.Yin H. map development using sequencing.Front. 12728169Crossref 45.Wu Scholar]MouseCxcl1/2/3/5/8, Ccl20, Ccl3l1, Il1rn, Il1b, G0s2, Inhba, Spp1N/ACT26 CRC CT26 modelChemokine productionImmunosuppressionscRNA-seq[45.Wu Scholar]LA-TAMsHumanACP5, AOPE, APOC1, ATF1, C1QA/B/C, CCL18, CD163, CD36, CD63, CHI3L1, CTSB/D/L, F13A1, FABP5, FOLR2, GPNMB, IRF3, LGALS3, LIPA, LPL, MACRO, MerTK, MMP7/9/12, MRC1, NR1H3, NRF1, NUPR1, PLA2G7, RNASE1, SPARC, SPP1, TFDP2, TREM2, ZEB1FOS/JUN HIF1A MAF/MAFB NR1H3 TCF4 TFECBRCACRCCRC metsGBMGCHCCHNCNPCNSCLCOSPDACPhagocytosisPromotion EMTComplement activationECM degradationAntigen processing pathwaysATP biosynthetic processesCanonical M2-like pathwaysFatty acid metabolismImmunosuppressionInflammationIron ion signalingscRNA-seqSMART-seq2CITE-seqmIHCST[12.Mulder Scholar,27.Zilionis R. cancers conserved populations individuals species.Immunity. 1317-1334Abstract (424) Scholar,28.Yang non-small differences sexes.Front. 12756722Google Scholar,30.Zhang analyses inform myeloid-targeted therapies colon 181: 442-459Abstract (246) Scholar,31.Che Scholar,50.Chen Y.P. subtypes associated prognosis carcinoma.Cell 30: 1024-1042Crossref (71) Scholar,81.Wu Scholar]CD9+, CD80+, MAF, CD163lo/-, CD206+/lo, CD71+, CD72+, CD73, ICOSL, CD40LG, Thy-1 (CITE-seq)MouseAcp5, Apoc1, Apoe, C1qa/B/C, Ccl18, Ccl8, Cd163, Cd206, Cd36, Cd63, Ctsb/d/l, Cxcl9, Fabp5, Folr2, Gpnmb, Lgals3, Macro, Mrc1, Trem2MAFCT26 Orthotopic GBM 7940b orthotopic iKras p53 PDAC metsPhagocytosisAntigen presentationFatty metabolismComplement activationscRNA-seqCITE-seqmIHC[45.Wu Scholar,46.Kemp S.B. al.Pancreatic marked complement-high blood tumor–associated macrophages.Life Alliance. 4e202000935Crossref Scholar]Angio-TAMsHumanADAM8, AREG, BNIP3, CCL2/4/20, CD300E, CD44, CD55, CEBPB, CLEC5A, CTSB, EREG, FCN1, FLT1, FN1, HES1, IL8, MIF, OLR1, PPARG, S100A8/9/12, SERPINB2, SLC2A1, SPIC, THBS1, TIMP1, VCAN, VEGFABACH1 CEBPB FOSL2 HIFA KLF5 MAF RUNX1 SPIC TEAD1 ZEB2BRCACRCCRCCRC metsESCAGBMGCHCCMELNPCNPCNSCLCOVCPDACPDAC metsRCCSEPNTHCAUCECAngiogenesisCAF interactionECM proteolysis; ECM interactionPromotion EMTHIF pathway; NF-kB Notch VEGF signalingJuxtaposed PLVAP+/DLL4+ endothelial (IF)scRNA-seqSMART-seq2CITE-seqNanoString GeoMx[25.Cheng Scholar,41.Sharma al.Onco-fetal drives carcinoma.Cell. 183: 377-394Abstract (103) Scholar,49.Raghavan al.Microenvironment drug 6119-6137Abstract Scholar,67.Zhao revealed promoted progression.J. Transl. 454Crossref Scholar]CD52hi, CD163hi, CD206hi, CXCR4+, CD354+, FOSL2, VEGFAMouseArg1, Adam8, Bnip3, Mif, Slc2a1N/AOrthotopic modelHIF signalingAngiogenesisscRNA-seqCITE-seq[52.Pombo Scholar]Reg-TAMsHumanCCL2, CD274, CD80, CHIT1, CX3CR1, HLA-A/C, HLA-DQA1/B1, HLA-DRA/B1/B5, ICOSLG, IL-10, ITGA4, LGALS9, MAC

Language: Английский

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Tumor Microenvironment Dynamics in Clear-Cell Renal Cell Carcinoma

Cancer Discovery, Journal Year: 2019, Volume and Issue: 9(10), P. 1349 - 1357

Published: Sept. 16, 2019

Abstract Renal cell carcinoma stands out as one of the most immune-infiltrated tumors in pan-cancer comparisons. Features tumor microenvironment heavily affect disease biology and may responses to systemic therapy. With evolving frontline options metastatic setting, several immune checkpoint blockade regimens have emerged efficacious, there is growing interest characterizing features that can reproducibly prognosticate patients and/or predict likelihood their deriving therapeutic benefit. Herein, we review pertinent characteristics with dedicated attention candidate prognostic predictive signatures well possible targets for future drug development. Significance: Tumor broadly angiogenesis inflammatory shown striking differences response antiangiogenic agents. Integration stromal biomarkers hence produce guide management existing

Language: Английский

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